ggplot2 package

What is ggplot2?

Its a package in R called ‘ggplot2’
An implementation of the grammar of graphics: a description of how a graphics can be broken down into abstract concepts.

From ggplot2 book: “In brief, the grammar tells us that a statistical graphic is a mapping from data to aesthetic attributes (colour, shape, size) of geometric objects (points, lines, bars). The plot may also contain statistical transformations of the data and is drawn on a specific coordinate system.”

Written by Hadley Wickham

qplot()

Stands for quick plot
Looks very similar to plot() function
Needs a data frame.
Plots are made up of aesthetics(size, shape, color) and geoms(points, lines).
Geoms: geometric objects to represent observations
Factors are very important in ggplot: make sure they are labeled in a meaningful way.
ggplot is the core function and can do things that qplot() can not do.

An example

The diamond example: the data set is available under the package ggplot2.

This dataset containing the prices and other attributes of almost 54,000 diamonds.

library(ggplot2)
qplot(carat, price, data = diamonds)

# compared to
plot(diamonds$carat,diamonds$price, type = 'p')

qplot(log(carat), log(price), data = diamonds)

dsmall <- diamonds[sample(nrow(diamonds), 300), ]
qplot(log(carat),log(price), colour = color, data = dsmall)

#diamonds example
qplot(carat, price, data = diamonds)

qplot(log(carat), log(price), data = diamonds)

qplot(carat, x * y * z, data = diamonds)

set.seed(1410)
dsmall <- diamonds[sample(nrow(diamonds), 100), ]
qplot(carat, price, data = dsmall)

qplot(log(carat), log(price), data = dsmall)

#modifying aesthetics: separate groups by the color of the diamonds. 
qplot(log(carat),log(price), colour = color, data = dsmall)

# separate groups by the shape
qplot(log(carat),log(price), shape = cut,data = dsmall)

#geom arguments adding some statistics "smoothing the data"
qplot(carat, price, geom = c("point", "smooth"), data = dsmall)

#histogram
qplot(carat, data = diamonds, geom = "histogram")

qplot(carat, data = diamonds, geom = "density")

#histogram
qplot(carat, data = diamonds, geom = "density", colour = color)

qplot(carat, data = diamonds, geom = "histogram", fill = color)

#facets
qplot(carat, data = diamonds, geom = "density",facets = color~.)

qplot(carat, data = diamonds, geom = "histogram", colour = color, facets = color~.)

qplot(carat,price, data = diamonds, facets = color~.)

qplot(carat,price, data = diamonds, facets = .~cut)

qplot(log(carat), log(price), data = dsmall, facets = cut~., 
      geom = c("point", "smooth"), method = 'lm', colour = cut)

ggplot()

When we used qplot(), it did a lot of things for us: it created a plot object, added layers, and displayed the result, using many default values along the way.

Some basics about ggplot() function:

Needs a data frame
aesthetic mappings: size, color
geoms: geometric objects
facets: multiple panels
stats: statistical transformations

Plots are built up in layers:

Plot the data
Overlay a summary: a statistics summary, regression line
Annotations

We just learned that:

qplot(log(carat), log(price), data = dsmall, facets = cut~., 
      geom = c("point", "smooth"), method = 'lm', colour = cut)

Now, we learn how to build with ggplot() function: Building ggplot(), adding things “piece by piece”:

g = ggplot(dsmall, aes(log(carat), log(price))) 
g = ggplot(dsmall, aes(log(carat), log(price))) +  geom_point()

Adding a smoother:

g + geom_point() + geom_smooth()

Adding another smoother:

g + geom_point() + geom_smooth(method = 'lm')

Adding Facets: the variable determines how the plots are separated:

g + geom_point() +facet_grid(cut~.)+geom_smooth(method = 'lm')

Adding Colors:

g + geom_point(aes(colour = cut)) +facet_grid(cut~.) + geom_smooth(method = 'lm')

g1 <- ggplot(dsmall, aes(log(carat), log(price), colour = cut))
g1 + geom_point() +facet_grid(cut~.) + geom_smooth(method ='lm')

### Remarks:

Orders do not matter
Make sure that your data has meaningful factor levels.

Some other changes could be done to your plot:

Modifying Aesthetics: g + geom_point(aes(colour = cut), size = 4, alpha = 1/4)
Annotation: You can change the labels of x, y axis by adding xlab(), ylab(), ggtitle() *. The background of your ggplot can be changed using theme_gray() default setting theme_bw() ---change to black
```
```r
g = ggplot(dsmall, aes(log(carat), log(price)))
g  + geom_point(aes(colour = cut)) + facet_grid(cut~.) + 
geom_smooth(method = 'lm', aes(colour = cut)) + theme_bw()
```

<img src="lecture7_files/figure-html/unnamed-chunk-11-1.png" title="" alt="" width="672" />
```
. Change the font by {r} base_family = "Times" . You can also delete your legend by issuing theme(lengend.position = "none"")